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Hitting the (bio)mark part 1: selecting and measuring biomarkers in cardiovascular research.

Bo DaelmanBrittany ButtsQuin E Denfeld
Published in: European journal of cardiovascular nursing (2024)
Cardiovascular studies, including nursing research, frequently integrate biomarkers for diagnostic, prognostic, monitoring and therapeutic insights. However, effective utilization of biomarker data demands careful consideration. In the study design phase, researchers must select biomarkers that align with study objectives while considering resources and logistical factors. Additionally, a nuanced understanding of disease pathophysiology and biomarker characteristics is needed. During data collection, suitable experimental conditions and assays need to be defined. Whether researchers opt to manage these steps internally or outsource some, a comprehensive understanding of biomarker selection and experiments remains crucial. In this article, part 1 of 2, we provide an overview of considerations for the design to measurement phases of biomarker studies.
Keyphrases
  • electronic health record
  • healthcare
  • mental health
  • high throughput
  • machine learning
  • deep learning
  • single cell